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Linear scaling between microbial predator and prey densities in the global ocean
Harshana Rajakaruna1, Anne Willem Omta2, Eric Carr1
1Department of Microbiology, University of Tennessee, Knoxville, TN, USA.
Environmental Microbiology
|November 6, 2022
Summary
Marine microbial predator-prey relationships are linear, not sublinear as previously thought. Ratios of predator to prey biomass remain invariant across different scales, challenging existing ecological hypotheses.
Area of Science:
- Marine ecology
- Microbial ecology
- Ecological stoichiometry
Background:
- Previous studies proposed sublinear power laws for microbial predator-prey biomass and abundance.
- These relationships are crucial for understanding marine food web dynamics and microbial loop functioning.
Purpose of the Study:
- To re-evaluate the biomass scaling relationships between marine microzooplankton predators and phytoplankton prey (Z/P).
- To re-evaluate the biomass scaling relationships between marine viral predators and bacterial prey (V/B).
- To test the hypothesis of sublinear power laws against alternative models.
Main Methods:
- Analysis of previously published biomass and abundance data.
- Fitting Power-law Biomass Scaling Relationships (PBSRs) using Type II regression models.
- Type II regression accounts for errors in both independent and dependent variables, unlike conventional Type I regression.
Main Results:
- Data support linear relationships between predator and prey biomass, contradicting previous sublinear findings.
- The scaling exponent has an expected value of 1, with variations described by a Gaussian distribution.
- The ratios of microzooplankton to phytoplankton (Z/P) and viral to bacterial (V/B) biomass are, on average, invariant.
Conclusions:
- The findings challenge the hypothesis that predator/prey ratios systematically decrease with increasing prey biomass.
- Microbial predator-prey biomass scaling is characterized by linear relationships and invariant ratios.
- This suggests a fundamental difference in how microbial communities scale compared to previous assumptions.
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